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510(k) Data Aggregation
(431 days)
FS-500DDR Medical Radiographic X-Ray System is designed to be used by a qualified/trained doctor or technician on adult and pediatric patients for taking diagnostic images of the skull, spinal column, extremities and other body parts. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position.
The FS-500DDR is a Medical Radiographic X-Ray System with digital radiography (DR) technology. It is consisting of a high voltage generator, control console, X-Ray tube assembly, collimator, UC bracket or Rail suspension assembly, solid-state X-Ray flat panel detector, work station and radiographic table. This product is applicable to clinical diagnostic radiography in all hospitals whether large or small. It is applicable to the radiography of various parts of human body. It can also be used in scientific research and education of medical scientific research institutes and medical colleges.
The provided text describes the FS-500DDR Medical Radiographic X-Ray System. However, it does not include detailed acceptance criteria or a specific study that proves the device meets those criteria in the way typically expected for an AI/ML medical device.
The document primarily focuses on demonstrating substantial equivalence to predicate devices for regulatory clearance, primarily through safety and performance standards compliance, and a "clinical concurrence study." It lacks the granular detail of acceptance criteria, performance metrics, and study methodology often found in AI/ML performance evaluations.
Therefore, I cannot populate the table and answer all questions comprehensively as the requested information is largely absent. I will extract what is available and highlight the missing information.
1. A table of acceptance criteria and the reported device performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Specific quantitative acceptance criteria for diagnostic performance (e.g., sensitivity, specificity, AUC) are not provided in the document. | The document states: "Clinical concurrence study of images pairs to demonstrate the equivalent diagnostic capability." This implies that the images produced by the FS-500DDR were deemed diagnostically equivalent, but no specific metrics or thresholds are given. |
| Compliance with various safety and performance standards (e.g., EN 60601-1, IEC 60601-2-7, IEC 60601-2-54, ISO 10993) | "After analyzing both bench and external laboratory testing data, including electrical safety, mechanical safety and EMC compliance, the intended use and supporting data can conclude that the device in the submission is safe and effective as the predicate devices." (Implies compliance was met, but no specific test results are provided.) |
2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)
- Sample Size for Test Set: Not specified. The document only mentions a "clinical concurrence study of images pairs."
- Data Provenance: Not specified (e.g., country of origin, retrospective or prospective).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)
- Number of Experts: Not specified.
- Qualifications of Experts: Not specified. The study involved a "qualified/trained doctor or technician" for operation, implying medical professionals, but their role in establishing ground truth for the "concurrence study" is not detailed.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
- Adjudication Method: Not specified.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
- MRMC Study: No. The device described is a medical radiographic X-ray system, not an AI/ML diagnostic aid designed to assist human readers. Therefore, an MRMC study comparing human readers with and without AI assistance is not applicable to this submission. The "clinical concurrence study" was likely to assess image quality for diagnostic equivalence, not reader performance improvement with AI.
- Effect Size of AI assistance: Not applicable.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done
- Standalone Study: Yes, in the sense that the device itself is a standalone imaging system. The performance evaluated was of the X-ray system producing diagnostic images, not an algorithm's interpretation of those images. The "clinical concurrence study" evaluated the diagnostic capability of the images produced by the device without human interpretation being directly compared against an AI algorithm's interpretation.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- Type of Ground Truth: Implied to be expert diagnostic assessment based on the "clinical concurrence study of images pairs to demonstrate the equivalent diagnostic capability." The specific method of establishing this "ground truth" (e.g., consensus, comparison to a gold standard, pathology) is not detailed.
8. The sample size for the training set
- Sample Size for Training Set: Not applicable. This is an X-ray imaging system, not an AI/ML algorithm that requires a training set in the conventional sense.
9. How the ground truth for the training set was established
- How Ground Truth for Training Set was Established: Not applicable.
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